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Foundational Standard

AI Education Assessment Alignment Framework

AAB foundational framework for aligning learning outcomes, assessment evidence, and credential claims

Summary

Connects learning outcomes with assessment methods and credential claims so AAB recognition language remains proportional to the evidence collected.

Key evidence signals

  • Assessment claims should name the learner audience, method, validity boundary, and evidence expected.
  • Participation, attendance, tool use, and full AI literacy mastery are different evidence claims.
  • Portfolio artifacts, scenario tasks, reflections, and rubrics can support stronger alignment than participation alone.

Recommendations

  1. State what each assessment or credential actually proves.
  2. Use age-band and role-specific evidence expectations.
  3. Align credentials with observable learner work and documented human review.